Beyond the Algorithm: Fostering Inclusive and Culturally Responsive Education for Multilingual and Multicultural Learners

Background of the Study Artificial intelligence (AI) has transformed the way teaching and learning occur in formal and informal settings. Simultaneously, classrooms across global contexts continue to welcome students from various linguistic and cultural backgrounds due to the shifting global dynamics around us. With a wide range of AI platforms currently utilised worldwide, the question of whether AI is creating inclusive spaces for multilingual and multicultural students remains unanswered. AI tools can support multilingual and multicultural students by personalising learning journeys, enhancing efficiency and access to resources and differentiating instruction. Despite that, AI tools are influenced by social, cultural and institutional factors, and there is growing concern that AI might cause further inequalities among traditionally marginalised students, especially when dominant languages and cultures are privileged and algorithmic bias is embedded. Objectives This study critically examines the extent to which AI supports or undermines equity, diversity and inclusion in multilingual and multicultural educational settings, grounded in culturally responsive pedagogy, translanguaging theory and critical digital pedagogy. Methods Utilising a systematic literature review informed by PRISMA guidelines, the study examines how AI use overlaps with issues of equity, diversity and inclusion in multilingual and multicultural settings. Results Findings identified recurring concerns across literature related to monolingual design bias, cultural misrepresentation in AI‐generated content, algorithmic representational harm and constraints on learner agency and access. These findings informed the development of the IHSAN Framework (Identity, Humanity, Safety, Access and Nuance), presented as a conceptual model in the Discussion. Conclusions The study recommends shared accountability among educators, AI developers, educational institutions and policymakers through culturally responsive AI design, equitable implementation practises and governance structures that protect linguistic diversity and learner access.